基于人物图像视觉特征的人物性格隐私分析

doi:10.11959/j.issn.1000-436x.2016223

Abstract

Abstract:

Personalized recommendation in social media attempts to analyze the habits and personality based on the loca-tion information and pictures from the users' comments on the public platform. This is very useful for personalized in-formation recommendation. But from perspective of privacy protection, this will affect the privacy security. A novel hu-man personality privacy analysis method based on portrait was proposed. By analyzing the personality model of the psy-chology, five visual features were proposed, including color features, texture features, shape features, Itten contrast fea-tures and expression features. Comprehensive experiments demonstrate the effectiveness of the proposed method. Further, the features analysis experiment show that the proposed features are very relevant to human personality privacy analyz-ing.

Key words: portrait, visual feature, personality, privacy

Jie NIE,Lei HUANG,Zhen LI,Jian ZHANG,Yan YAN,Zhi-qiang WEI. Human personality privacy analysis based on visual features[J]. Journal on Communications, 2016, 37(11): 129-136.

Figures/Tables 9

References 22

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序号	名称	长度	描述
1	色调、饱和度、亮度	42	所有图像区域的（7个）在色调、饱和度和亮度3个通道的均值和方差
2	PAD特征	6	全图和服装区域在pleasure、arousal和dominance 3个维度的特征
3	灰度共生矩阵（GLCM）	20	全图、面部区域、发型区域和鼻嘴区域、服装区域的特征
4	Tamura特征	30	全图、面部区域、发型区域和鼻嘴区域、服装区域的特征
5	边缘直方图	84	所有图像区域（7个）的边缘进行梯度统计，将360°平均划分为12个单元
6	方向梯度直方图（HOG）	84	眼部区域（24）、眉毛区域（24）、鼻嘴区域（36）进行统计
7	伊顿对比特征	21	详见表2
8	表情特征	1	生气(anger)、厌恶(disgust)、害怕(fear)、微笑(smile)、大笑(laugh)、伤心(sadness)、惊讶(surprise)和中立(neutral)

对比特征	符号	区域对
色度对比	H_Itten	全图和服装，全图和面部，面部和鼻嘴部，面部和服装，面部和发型，发型和服装
亮度对比	L_Itten	全图和面部，面部和服装，眼部和鼻嘴部
饱和度对比	S_Itten	全图和面部，面部和服装，眼部和鼻嘴部
带权重的亮度对比	L_Itten_weighted	全图和面部，面部和服装，眼部和鼻嘴部
冷暖对比	U_Itten	全图和服装，全图和面部，面部和鼻嘴部，面部和服装，面部和发型，发型和服装

人格类型	有效样本总数	样本数量（+/?）
经验开放性(O)	1 876	564/1 312
尽责性(C)	1 543	873/670
外倾性(E)	1 679	742/973
宜人性(A)	1 849	321/1 528
情绪稳定性(N)	1 753	599/1 154

序号	特征名称	O	C	E	A	N
1	色调	●	●	●	●	●
2	饱和度		●	●		●
3	亮度		●	●		●
4	全图．PAD	●	●	●	●	●
5	服装．PAD	●	●	●	●
6	全图．GLCM		●	●
7	面部．GLCM		●	●
8	发型．GLCM		●	●
9	鼻嘴．GLCM		●	●		●
10	服装．GLCM	●	●	●	●
11	全图．Tamura		●	●	●
12	面部．Tamura		●	●	●	●
13	发型．Tamura		●	●
14	鼻嘴．Tamura		●	●
15	边缘直方图		●	●
16	眼部．HOG		●	●
17	眉毛．HOG		●	●		●
18	鼻嘴．HOG		●	●	●	●
19	全图和服装．伊顿色度	●	●	●	●	●
20	全图和面部．伊顿色度	●	●	●	●	●
21	面部和鼻嘴部．伊顿色度		●	●		●
22	面部和服装．伊顿色度	●	●	●	●	●
24	面部和发型．伊顿色度		●	●	●
25	发型和服装．伊顿色度		●	●		●
26	全图和面部．伊顿亮度	●	●	●	●
27	面部和服装．伊顿亮度		●	●	●
28	眼部和鼻嘴部．伊顿亮度	●	●	●	●
29	全图和面部．伊顿饱和度		●	●
30	面部和服装．伊顿饱和度		●	●
31	眼部和鼻嘴部．伊顿饱和度	●	●	●	●
32	全图和面部．伊顿亮度（权重）	●	●	●	●	●
33	面部和服装．伊顿亮度（权重）	●	●	●	●	●
34	眼部和鼻嘴部．伊顿亮度（权重）		●	●		●
35	全图和服装．伊顿冷暖	●	●	●	●	●
36	全图和面部．伊顿冷暖	●	●	●	●	●
37	面部和鼻嘴部．伊顿冷暖		●	●		●
38	面部和服装．伊顿冷暖		●	●		●
39	面部和发型．伊顿冷暖		●	●	●	●
40	发型和服装．伊顿冷暖	●	●	●	●	●
41	表情特征	●	●	●	●	●
	特征选择方法	G	P	P	G	G

人格类型	主观方法	本文方法	基准方法
经验开放性(O)	78.83%	61.75%	49.81%
尽责性(C)	81.75%	67.47%	62.15%
外倾性(E)	89.33%	74.75%	68.63%
宜人性(A)	85.15%	55.96%	52.33%
情绪稳定性(N)	75.18%	66.77%	64.16%

Human personality privacy analysis based on visual features

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